The jobs puzzle: Taking on the challenge via controlled natural language processing
2013 ◽
Vol 13
(4-5)
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pp. 487-501
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Keyword(s):
AbstractIn this paper we take on Stuart C. Shapiro's challenge of solving the Jobs Puzzle automatically and do this via controlled natural language processing. Instead of encoding the puzzle in a formal language that might be difficult to use and understand, we employ a controlled natural language as a high-level specification language that adheres closely to the original notation of the puzzle and allows us to reconstruct the puzzle in a machine-processable way and add missing and implicit information to the problem description. We show how the resulting specification can be translated into an answer set program and be processed by a state-of-the-art answer set solver to find the solutions to the puzzle.
2018 ◽
Vol 18
(3-4)
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pp. 691-705
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2015 ◽
Vol 21
(5)
◽
pp. 699-724
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2012 ◽
Vol 45
(5)
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pp. 825-826
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Keyword(s):